Methods and apparatus to identify media using hybrid hash keys

ABSTRACT

Methods and apparatus are disclosed to identify media using hash keys. An example disclosed method includes generating a hash key based on first samples of media. In the disclosed example method, the first samples corresponds to a portion of the media sampled in a buffer of a computing device. The example method also includes applying a blurring function to the hash key to generate a blurred hash key. The example method also includes generating first confirmation data based on second samples of the media. The example method also includes storing the blurred hash key in association with the first confirmation data and first reference data in a memory separate from the buffer of the sampled media. In the example methods, the reference data identifies the portion of the media.

FIELD OF THE DISCLOSURE

This disclosure relates generally to audience measurement and, moreparticularly, to methods and apparatus to identify media using hashkeys.

BACKGROUND

Audience measurement of media, such as television, music, movies, radio,Internet websites, streaming media, video games, etc., is typicallycarried out by monitoring media exposure of panelists that are selectedto represent a particular demographic group. The captured media exposuredata is processed using various statistical methods to determineaudience size and demographic composition(s) for programs of interest.The audience size and demographic information is valuable toadvertisers, broadcasters and/or other entities. For example, audiencesize and demographic information may be used as factors in selecting theplacement of advertisements, and may be used as factors in valuingcommercial time slots during a particular program.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example system constructed in accordance with theteachings of this disclosure and having a media meter in communicationwith an audience measurement entity to monitor media presentations.

FIG. 2 illustrates the example reference hash key generator of FIG. 1which may be used to generate the example reference records of FIGS. 3Aand/or 3B.

FIGS. 3A and 3B illustrate example configurations of the referencedatabase of FIG. 1 that may be used to store reference metadata inassociation with reference hash keys of corresponding media.

FIG. 4 illustrates an example diagram that depicts generating theexample reference records of FIGS. 3A and/or 3B.

FIG. 5 illustrates an example implementation of the example hash keyidentifier of FIG. 1 which may be used to compare metered hash keys withreference hash keys to generate a monitoring report and/or to storeimpressions in a monitoring database.

FIG. 6 is a flow diagram of example machine readable instructions thatmay be executed to implement the hash key manager of FIGS. 1 and/or 5 tocompare metered hash keys to reference hash keys.

FIG. 7 is another flow diagram of example machine readable instructionsthat may be executed to implement the hash key manager of FIGS. 1 and/or5 to compare metered hash keys to reference hash keys.

FIG. 8 is a flow diagram of example machine readable instructions thatmay be executed to implement the reference hash key generator of FIGS. 1and/or 2 to generate reference hybrid-hash keys.

FIG. 9 is a block diagram of an example processor system that mayexecute any of the machine readable instructions represented by FIGS. 6,7, and/or 8 to implement the apparatus of FIGS. 2 and/or 5.

DETAILED DESCRIPTION

Examples disclosed herein may be used to identify media (e.g., movies,music, television programs, radio programming, televisionadvertisements, radio advertisements, video games, etc.) using hash keysassociated with the media. To create indexable identifiers for portionsof media of interest, in examples disclosed herein, the media is sampledat a particular frequency (e.g., 15 kHz, 30 kHz, 64 kHz, etc.). Usingone or more fingerprinting techniques, such as robust audio hashing,hash keys are generated based on the samples of the media. In somerobust audio hashing examples, binary values represent differences inenergy between frequency bands of a sample. In some such examples, ahash key has a length in bits corresponding to the number of energybands used to create the hash key (e.g., a 64-bit length hash keycorresponds to the differences between 65 energy bands). Samples of themedia may be hashed, for example, in accordance with the techniquesdescribed by Haitsma et al. in an article entitled, “Robust AudioHashing for Content Identification.”

To generate reference hash keys, a reference version of media is sampledat a sampling frequency (e.g., 15 kHz, 30 kHz, 64 kHz, etc.). In someexamples, reference media is media (e.g., a song, a television program,a radio program, a video and/or audio spot or clip, an advertisement,streaming media, etc.) that has the same or higher quality than mediatypically obtained by and/or presented to a user. In some examples, thereference media is free from noise (e.g., white noise, pink noise, brownnoise, etc.) and/or is stored and/or decoded using a lossless format(e.g., Free Lossless Audio Codec (FLAC), Waveform Audio File Format(WAV), Apple® Lossless Audio Codec (ALAC), etc.). For example, areference version (or reference media) of audio (e.g., collected in acontrolled environment, such as a studio) may be a high quality,lossless digital copy of the song relative to whereas a streamed version(e.g., measured media) of the same audio will typically exhibit lowerquality and less accuracy in its reproduction and playback due toenvironmental noise, transmission losses, etc.

In some examples, an audience measurement entity (AME) contacts and/orenlists panelists using any desired methodology (e.g., random selection,statistical selection, phone solicitations, Internet advertisements,surveys, advertisements in shopping malls, product packaging, etc.).Demographic information (e.g., gender, occupation, salary, race and/orethnicity, marital status, highest completed education, currentemployment status, etc.) is obtained from a panelist when the panelistjoins (i.e., registers for) a panel. Additionally or alternatively,demographic information may be obtained through other methods during anenrollment process (e.g., via a telephone interview, by having thepanelist complete an online survey, etc.). In some examples, the AMEprovides a media meter (e.g., a set top meter, a personal portable meter(PPM), an on-device meter, a portable media player meter, etc.) to thepanelist after the panelist enrolls into the panel.

In some examples, the media meters collect metered samples by samplingmedia from media sources that are within sufficient detection proximityto the meter. For example, a set top meter may sample audio from a moviepresented via a media presentation device, such as a television locatedin the same room as the set top meter, or a portable media player metermay sample audio presented via a media presentation device such as aportable media player (e.g., an MP3 player, an Apple® iPod®, etc.). Insome examples, the sample is captured using a microphone of the mediameter. In some examples, the media meter obtains the metered samplethrough a wired connection (e.g., to an audio out jack) via a splitteror an in-line configuration via which the media meter interceptsportions of the media as they are communicated between a media sourceand headphones, etc. In some examples, the media samples are sampled bythe media meters at the same frequency as the reference samples weresampled. In some examples, the metered samples are sent to a centraloffice of the AME where metered hash keys are generated based on themetered samples. In some examples, the media meter is provided with ahash key generator to locally generate metered hash keys. In some suchexamples, the media meter sends metered hash keys to the central office.

In examples disclosed herein, a reference record is constructed bygenerating a reference hash key for a sample of reference media. In someexamples, the reference hash key may be 40-bits long or 64-bits long.Metadata (e.g., the name of the corresponding media, a time and/oroffset in the media corresponding to the sample, etc.) related to thesample is stored in the reference record in association with thereference hash key. The reference records also includes confirmationdata that corresponds to the reference hash key. The confirmation datais another sample of the reference media that is related to the sampleused to generate the reference hash key. For example, the confirmationdata may be 32-bits of the reference media sample that immediatelyfollow the sample used to generate the reference hash key. In someexamples, a blurring function is applied to the reference hash key. Theblurring function reduces the specificity of the reference hash key inorder to increase error tolerance of the reference hash key. Because thespecificity of the reference hash key is reduced, one of the referencehash keys may be associated with multiple sets of metadata.Additionally, in some examples, samples of more than one of the mediamay, by coincidence, produce the same reference hash key. In suchexamples, the confirmation data is used to distinguish between identicalreference hash keys.

Errors may arise in the media presentation before the media presentationis sampled by a media meter. For example, converting media from alossless format (e.g., Free Lossless Audio Codec (FLAC), Waveform AudioFile Format (WAV), Apple® Lossless Audio Codec (ALAC), etc.) to a lossyformat (e.g., MPEG Audio Layer III (MP3), Advanced Audio Coding (AAC),Ogg Vorbis, etc.) may change the media sufficiently so that a meteredhash key generated based on a portion (e.g., a segment) of thelossy-format media is different from a reference hash key correspondingto a non-lossy format of the same portion (e.g., the same segment) ofthe media. Additionally or alternatively, ambient noise and/orattenuation may also introduce errors into samples of the measuredmedia. Transmission errors may also be a source of errors in meteredhash keys. These sources of noise, loss and/or error may cause one ormore bits of the metered hash key to be different relative to acorresponding reference hash key.

In some examples, the blurring function may set one or more of the leastsignificant bits in each byte of the reference hash key to zero becausethe least significant bit(s) of the bytes that make up the hash key aremost prone to noise during the hash key generating process. In someexamples, the number of bits set to zero depends on the byte-length ofthe reference hash key. For example, if the reference hash key is40-bits long, the blurring function may set the least significant bit ofeach byte to zero. Alternatively, for example, if the reference hash keyis 64-bits long, the blurring function may set the two least significantbits of each byte to zero. For example, by blurring the leastsignificant bit, if the generated reference hash key is 0x 0D 73 E1 BD(binary: 00001101 01110011 11100001 10111101), the blurred referencehash key would be 0x 0C 72 E0 BC (binary: 00001100 01110010 1110000010111100).

In examples disclosed herein, the media meter generates metered hashkeys and corresponding confirmation data. In such examples, theconfirmation data generated by the media meter has the same length andoffset as the confirmation data generated for the reference hash keys.In some examples, the media meter blurs the generated metered hash keysusing the same blurring function applied to the reference hash keys tothe generated metered hash keys. Alternatively, in some examples, themedia meter sends the metered hash keys without applying the blurringfunction and the blurring function is applied to the generated meteredhash keys before the metered hash key is compared to the reference hashkeys.

In examples disclosed herein, the AME receives metered hash keys andcorresponding confirmation data from the media meter and compares themetered hash keys to reference hash keys in the reference hash table. Ifa metered hash key is found in the reference hash table, theconfirmation data corresponding to the metered hash key is compared tothe confirmation data corresponding to the reference hash key. If theconfirmation data corresponding to the metered hash key matches theconfirmation data corresponding to the reference hash key, an impressionfor corresponding media (e.g., reference media corresponding to thematching reference hash key) is logged. In some examples, metadatacorresponding to the reference hash key is retrieved from acorresponding reference record, and the metadata is stored inassociation with the logged impression. In some examples, information(e.g., demographics, panelist ID, etc.) associated with one or morepanelists and/or a timestamp indicative of a time at which the meteredmedia was presented is stored in association with the logged impression.

In examples disclosed herein, when the metered hash key is compared tothe reference hash keys in the reference hash key table, multiplecandidate reference hash keys may exist. For example, when the referencehash keys are generated, the least significant bit is blurred. As such,a reference hash key of 0x0C 72 E0 BC may correspond to the followingnon-blurred reference hash keys: 0x0C 73 E0 BC, 0x0D 73 E0 BC, 0x0D 72E0 BC, 0x0C 72 E0 BD, 0x0C 73 E0 BD, 0x0D 73 E0 BD, 0x0D 72 E0 BD, 0x0C72 E1 BD, 0x0C 73 E1 BD, 0x0D 73 E1 BD, 0x0D 72 E1 BD, 0x0C 72 E1 BC,0x0C 73 E1 BC, 0x0D 73 E1 BC, and 0x0D 72 E1 BC. In such examples, whenmultiple candidate reference hash keys exist in the reference hash keytable, the confirmation data corresponding to the metered hash key iscompared to the confirmation data corresponding to the reference hashkeys. In some such examples, error levels are calculated between theconfirmation data corresponding to the metered hash key and theconfirmation data corresponding to the reference hash keys. In suchexamples, metered hash key is determined to match the reference hash keythat has the lowest error level that satisfies (e.g., is less than,etc.) an error threshold.

FIG. 1 illustrates an example system constructed in accordance with theteachings of this disclosure and having the media meter 100 incommunication with the AME 102 to monitor media 104 presented by themedia presentation device 106. In the illustrated example, the mediameter 100 samples the example media 104 output by the example mediapresentation device 106 and generates example exposure records 108. Insome examples, a people meter 110 is associated with the media meter 100to identify persons in the audience at the time the exposure records 108are collected. In some examples, people identification data collected bythe people meter 110 is returned with the exposure records 108. Fromtime to time, the example media meter 100 sends the example exposurerecords 108 to the example AME 104 via an example network 112 (e.g., theInternet, a local area network, a wide area network, etc.) via wiredand/or wireless connections (e.g., a cable/DSL/satellite modem, a celltower, etc.).

In the illustrated example, the exposure records 108 include an examplemetered hash key 114, example metered confirmation data 116, an examplemedia meter identifier (ID) 118, and an example timestamp 120. In someexamples, the exposure records 108 also include identifiers associatedwith the persons in the audience as detected by the people meter(s) 110.The example metered hash key 114 is a value that characterizes a portionof the media 104 or is representative of a portion of the media 104 at acertain point in time (e.g., as indicated by the timestamp 120) of themedia 104. In some examples, the metered hash key 114 is taken from astream of the media 104. Alternatively, in some examples, the stream ofmedia 104 is preprocessed by a signature generation engine that hashesthe stream of the media 104. In such examples, the metered hash key 114is taken from the hashed stream of the media 104. In some examples, themedia meter 100 applies a blurring function after generating the hashkey 114. In such examples, the blurring function sets a number of leastsignificant bits in each byte of the hash key 114 to zero.

The example metered confirmation data 116 includes a number of bits ofthe media 104 offset from an end of the metered hash key 114 by a numberof bits. For example, the metered confirmation data 116 may includetwenty-four bits corresponding to a subsequent portion of the media 104following the portion of the media 104 corresponding to the metered hashkey 114. In the illustrated example, the media meter ID 118 is analphanumeric value which identifies (preferably uniquely) the mediameter 100 and/or one or more of the people associated with the peoplemeter 110. The example timestamp 120 corresponds to a time when theportion of the media 104 represented by the metered hash key 114 ispresented by the example media presentation device 106.

The AME 102 of the illustrated example includes an example meteringdatabase 122, an example hash key identifier 124, an example monitoringdatabase 126, an example reference database 128, and an examplereference hash key generator 130. The example exposure records 108 arecollected and stored in the example metering database 122.

As disclosed in more detail in FIG. 5 below, the example hash keyidentifier 124 compares the exposure records 108 to reference records inthe reference database 128 to identify the portion of the media 104corresponding to the metered hash key 114. When one of the exposurerecords 108 corresponds to one of the reference records, the examplehash key identifier 124 generates an impression. The impressionassociates the media meter ID 118 and/or the timestamp 120 to theportion of the media 104 (e.g., as a media segment ID) and/or metadataidentifying the portion of the media 104 corresponding to the matchingreference record.

As discussed in more detail in FIG. 2 below, the reference hash keygenerator 130 samples the reference media 132 (e.g., media that has thesame or higher quality than media 104 obtained by and/or presented to auser) to generate the reference hash keys. In some examples, thereference hash key generator 130 applies the burring function to thereference hash key. The example reference hash key generator 130 alsogenerates reference confirmation data using the same size and offset asthe media meter 100 uses to generate the metered confirmation data 116.The example reference hash key generator 130 creates reference recordsthat include the reference hash key and corresponding referenceconfirmation data. In the illustrated examples, the example referencehash key generator 130 stores the generated reference records createdbased on the reference hash keys in the example reference database 128.In some examples, the reference hash key generator 130 does not createthe reference confirmation data for particular ones of the referencehash keys at the beginning and/or at the end of the reference media 132because there are not enough samples of the reference media 132 togenerate the reference confirmation data.

FIG. 2 illustrates an example implementation of the example referencehash key generator 130 of FIG. 1. The example reference hash keygenerator 130 generates reference records 202 to be stored in theexample reference database 128. The example reference hash key generator130 includes an example hybrid hash key generator 204, an example hashkey modifier 206, and an example reference generator 208. The examplehybrid hash key generator 204 samples the reference media 130 at asampling frequency (e.g., 16 kHz, 32 kHz, 64 kHz, etc.).

The example hybrid hash key generator 204 generates reference hash keys210 based on the samples. The example reference hash keys 210 arerepresentative of a particular portion of the reference media. Theexample reference hash keys 210 are used as an index to identify thecorresponding portion of the reference media when compared to meteredhash keys. Additionally, the example hybrid hash key generator 204generates reference confirmation data 212 based on the samples. Theexample hybrid hash key generator 204 uses a size (e.g., in bytes) andan offset to determine which samples are to be used for the referenceconfirmation data 212. For example, the reference confirmation data 212may have a size of twenty-four bits and an offset of two bits. In suchan example, because the offset is two bits, the reference confirmationdata 212 begins at two bits from the end of the reference hash key 210to which the reference confirmation data 212 corresponds. In someexamples in which the offset is a negative number, the referenceconfirmation data 212 overlaps with the corresponding reference hash key210. The size and the offset are defined by the example AME 102 (FIG. 1)so that the size and offset used by the example hybrid hash keygenerator 204 are the same as the size and the offset used by theexample media meter 100 (FIG. 1) to generate there metered hash key 114and the metered confirmation data 116 of the exposure record 108 (FIG.1).

In some examples, when the size and the offset specify samples that arenot generated for the reference media 132 (e.g., at the end of thereference media 132), the hybrid hash key generator 204 does notgenerate the reference confirmation data 212. For example, if the sizeand the offset specify that 32-bits of the samples of the referencemedia 132 after the reference hash key 210 are to be used to generatethe reference confirmation data 212 and only 16-bits remain until theend of the reference media 132, the hybrid hash key generator 204 maynot generate the reference confirmation data 212. In some such examples,the hybrid hash key generator 204 may instead generate the referenceconfirmation data 212 with a placeholder value (e.g., 0x00 00 00 00,0xFF FF FF FF, 0xAA AA AA AA, etc.).

The example hash key modifier 206 applies the blurring function to thereference hash key 210 to generate a blurred reference hash key 214. Theblurring function sets a number of the least significant bits of eachbyte of the reference hash key 210 to zero. In some examples, the numberof bits that the hash key modifier 206 sets to zero depends on thebit-length of the reference hash key 210. For example, longer meteredhash keys 114 represent a greater degree of precision (e.g., 64-bitsrepresenting a portion of the media instead of 40-bits, etc.), but arealso more likely to have least significant bits subject to noise. Forexample, if the reference hash key 210 is 40-bits long, the hash keymodifier 206 may set the least significant bit of each byte of thereference hash key 210 to zero. Alternatively, for example, if thereference hash key 210 is 64-bits long, the hash key modifier 206 mayset the two least significant bits of each byte of the reference hashkey 210 to zero. For example, if the reference hash key 210 is 0x 37 01D2 02 2B 3D 5D 76 and if the least significant bit of each byte are setto zero, the blurred reference hash key is 0x 36 00 D2 02 2A 3C 5C 76.As another example, if the reference hash key 210 is 0x 37 01 D2 02 2B3D 5D 76 and if the two least significant bits of each byte are set tozero, the blurred reference hash key is 0x 34 00 D0 00 28 3C 5C 74. Byapplying the blur function, the example hash key modifier 206 makes theblurred reference hash key 214 less precise than the reference hash key210, but also makes the blurred reference hash key 214 more errortolerant than the reference hash key 210.

The example reference generator 208 receives or retrieves the blurredreference hash keys 214 and the reference confirmation data 212. Theexample reference generator 208 generates the example reference records202 that associate the blurred reference hash key 214 to correspondingreference media metadata 216 and the corresponding referenceconfirmation data 212. FIGS. 3A and 3B illustrate examples of thereference records 202 stored in the reference database 128. In theexample illustrated in FIG. 3A, the hash key modifier 206 does not applythe blurring function to the reference hash key 210. As such, theexample reference records 202 has a one-to-one relationship between oneof the reference hash keys 210, one set of reference metadata 216 (e.g.,a media ID, a station ID, a station call sign, a timestamp correspondingto a portion of the media 104, etc.) and the confirmation datum 212.

In the example illustrated in FIG. 3B, the hash key modifier 206 appliesthe blurring function to the reference hash key 210. As such, in theillustrated example, a single blurred reference hash key 214 can beassociated with multiple pairs of reference metadata 216 andconfirmation data 212. For example, the blurred reference hash key 214of “0xF8 00 D0 0A” may be associated with (a) the pair of referencemetadata 216 and confirmation data 212 including “KBLR,2015-01-12T11:04:59Z” and “0xC7 43 9D A2” respectively, and (b) the pairof reference metadata 216 and confirmation data 212 including “KGLA,2015-10-26T12:46:35Z” and “0xB0 F2 44 68” respectively. In the exampleillustrated in FIG. 3B, the number of least significant bits blurred bythe hash key modifier 206 and the number of bits in the reference hashkey 210, increase a likelihood that multiple portions of the media 104will have a reference hash key 210 that, when blurred, corresponds tothe same blurred reference hash key 214.

While an example manner of implementing the example reference hash keygenerator 130 of FIG. 1 is illustrated in FIG. 2, one or more of theelements, processes and/or devices illustrated in FIG. 2 may becombined, divided, re-arranged, omitted, eliminated and/or implementedin any other way. Further, the example hybrid hash key generator 204,the example hash key modifier 206, the example reference generator 208and/or, more generally, the example reference hash key generator 130 ofFIG. 1 may be implemented by hardware, software, firmware and/or anycombination of hardware, software and/or firmware. Thus, for example,any of the example hybrid hash key generator 204, the example hash keymodifier 206, the example reference generator 208 and/or, moregenerally, the example reference hash key generator 130 could beimplemented by one or more analog or digital circuit(s), logic circuits,programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example hybrid hashkey generator 204, the example hash key modifier 206, and/or the examplereference generator 208 is/are hereby expressly defined to include atangible computer readable storage device or storage disk such as amemory, a digital versatile disk (DVD), a compact disk (CD), a Blu-raydisk, etc. storing the software and/or firmware. Further still, theexample reference hash key generator 130 of FIG. 1 may include one ormore elements, processes and/or devices in addition to, or instead of,those illustrated in FIG. 2, and/or may include more than one of any orall of the illustrated elements, processes and devices.

FIG. 4 illustrates an example diagram that depicts an example manner ofhow the example reference records 202 of FIGS. 2, 3A and/or 3B may begenerated (e.g. by the reference hash key generator 130 of FIGS. 1 and2). The example illustrated in FIG. 4 depicts a data stream 402 thatincludes the samples of the reference media 132 (FIGS. 1 and 2) that areanalyzed by the reference hash key generator 130. The illustratedexample also depicts the media metadata 216 chronologicallycorresponding to the data stream 402. In some examples, the data stream402 may be stored in a buffer of the hybrid hash key generator 204 (FIG.2). In the illustrated example, the metadata 216 includes a media sourceidentifier 404, a date 406, and timestamps 408. The example media sourceidentifier 404 is a value (e.g., a call sign, a television channelnumber, a radio station tuning frequency, a media stream URL, etc.) thatidentifies the entity (e.g., broadcaster, streaming media service,producer, etc.) that is making the media 104 available. The examplehybrid hash key generator 204 analyzes the samples of the referencemedia 132 and produces the example data stream 402 which includes hashedvalues of the samples.

The example hybrid hash key generator 204 selects a first portion 410 ofthe data stream 402 corresponding to a timestamp 408 of interest to be areference hash key 210 (FIG. 2). For example, to generate a referencehash key 210 corresponding to a first time, the hybrid hash keygenerator 204 may select the first portion 410 having a value of 0xF9 00D1 0E corresponding to the timestamp 408 of 14:06:52. As anotherexample, to generate a reference hash key 210 corresponding to a secondtime, the hybrid hash key generator 204 may select an additional firstportion 412 with a value of 0xA6 7F D7 F1 corresponding to the timestamp408 of 14:06:53. In the illustrated example, the hash key modifier 206(FIG. 2) applies the blurring function 414 to transform the referencehash key 210 into the blurred reference hash key 214.

In the illustrated example, the hybrid hash key generator 204 selects asecond portion 416 of the example data stream 402 to be the referenceconfirmation data 212. The example location of the second portion 416 inthe data stream 402 is determined by an offset 418 and a size 420. Theexample offset 418 is a value, in bits, that defines the location of thesecond portion 416 relative to the first portion 410. For example, anoffset of sixteen would locate the start of the second portion 416sixteen bits (two bytes) of the data stream 402 chronologically afterthe first portion 410. In some examples, the offset 418 may be negative.For example, if the offset 418 is negative sixteen, the sixteen bits(two bytes) of the first portion 410 would be included in the secondportion 416. The example size 420 defines a quantity of bits that areincluded in the second portion 416. In some examples, the size 420 ofthe second portion 416 is a percentage (e.g., 25%, 50%, etc.) of thesize of the first portion 410. For example, if the size 420 of thesecond portion 416 is 25% of the size of the first portion 410, and thefirst portion 410 includes 40 bits, the size 420 of the second portion416 would be 10 bits. Alternatively, in some examples, the size 420 ofthe second portion 416 is a multiple (e.g., 1.25, 1.5, 2, etc.) of thesize of the first portion 410. For example, if the size 420 of thesecond portion 416 is 1.5 times the size of the first portion 410 andthe first portion 410 includes 40 bits, the size 420 of the secondportion 416 would be 60 bits. In the illustrated example, the examplereference generator 208 (FIG. 10) generates the reference records 202 byassociating the blurred reference hash key 214, the reference metadata216 corresponding to the blurred reference hash key 214, and thereference confirmation data 212.

FIG. 5 illustrates an example implementation of the example hash keyidentifier 124 of FIG. 1 which may be used to compare the exposurerecords 108 with the reference records 202 to generate a monitoringreport and/or to store impressions in the monitoring database 126. Thehash key identifier 124 of the illustrated example includes an examplehybrid hash key analyzer 502, an example error handler 504, and anexample impression logger 506. The example hybrid hash key analyzer 502of the illustrated example retrieves the exposure records 108 from theexample metering database 122 Initially, to generate an impression, theexample hybrid hash key analyzer 502 queries the reference database 128for the reference record(s) 202 that include(s) the reference hash keys210 (FIGS. 2 and 3A) and/or the blurred reference hash keys 214 (FIGS.2, 3B, and 4) that match the metered hash key 114 (FIG. 1) of theexposure record 108.

In the illustrated example, the hybrid hash key analyzer 502 comparesthe metered confirmation data 116 (FIG. 1) corresponding to the meteredhash key 114 to the reference confirmation data 212 (FIGS. 2, 3A, 3B,and 4) of the retrieved reference record(s) 202. In some examples inwhich the metered hash key 114 is blurred (e.g., by the meter 100 ofFIG. 1) and the blurred reference hash key 214 is blurred, the query ofthe reference database 128 may return more than one reference record202. Also, in some examples, the query of the reference database 128 mayreturn more than one reference record 202 because the samples of morethan one of the media 104 (FIG. 1) may, by coincidence, produce the samereference hash key 210. If the metered confirmation data 116 matches thereference confirmation data 212 of one of the retrieved referencerecords 202, the example hybrid hash key analyzer 502 sends the exampleexposure record 108 and the corresponding reference record 202 to theexample impression logger 506.

In the illustrated example, if the metered confirmation data 116 doesnot match the reference confirmation data 212 of one of the retrievedreference records 202, the error handler 504 determines an error levelbetween the metered confirmation data 116 and the reference confirmationdata 212 of each of the retrieved reference record 202. In someexamples, to generate the error level (e), the error handler 504performs a bitwise comparison (e.g., a bitwise exclusive OR, etc.)between the metered confirmation data 116 and the reference confirmationdata 212 using Equation 1 below.

e=BitCount(C _(m) ⊕C _(r))   Equation 1

In Equation 1 above, C_(m) is the metered confirmation data 116, C_(r)is the reference confirmation data 212, and the BitCount( ) functionreturns the number of ones in a binary number. For example, as shown inTable 1 below, if the metered confirmation data 116 is 0xA6 00 85 69 andif the reference confirmation data 212 is 0xA2 10 85 E9, the error level(e) is 3 (BitCount(0xA6008569⊕0xA21085E9)=3) because two bit positionshave non-matching values.

TABLE 1 EXAMPLE ERROR LEVEL (e) CALCULATION Hexadecimal Binary0xA6008569 1010 0110 0000 0000 1000 0101 0110 1001 ⊕ 0xA21085E9 10100010 0001 0000 1000 0101 1110 1001 0x04100080 0000 0100 0001 0000 00000000 1000 0000

The example error handler 504 selects one of the retrieved referencerecords 202 corresponding to the corresponding reference confirmationdata 212 having an error level that is the smallest of the calculatederror levels that is less than an error threshold. The example errorlevel is indicative of the number of bits that are different between thereference confirmation data 212 and the metered confirmation data 116.In some examples, the error threshold is be set to a percentage (e.g.5%, 10%, etc.) of the bit length of the metered hash key 114. Forexample, an error threshold of 4 bits may be selected for a 40-bitmetered hash key 114. Table 2 below illustrates an example of referenceconfirmation data 212 and the associated error levels (e).

TABLE 2 EXAMPLE ERROR LEVELS (e) CALCULATED FOR EXAMPLE REFERENCERECORDS Metered Confirmation Data 0x6B BE 95 F0 Reference ConfirmationData Error Level (e) First Reference Record 0x7B BB 95 F0 2 bits SecondReference Record 0x6F BE 9D D8 4 bits Third Reference Record 0x9C 28 71A3 19 bits In the example illustrated in Table 2 above, the error handler 504 wouldselect the First Reference Record because the Error Level (e) for theFirst Reference Record is the lowest error level.

In the illustrated example of FIG. 5, the impression logger 506retrieves or otherwise receives the exposure record 108 and the selectedreference record 202 from the example hybrid hash key analyzer 502. Theimpression logger 506 creates an impression record 508 by associatingthe meter ID 118 and the timestamp 120 of the exposure record 108 withthe reference metadata 216 of the reference record 202. In theillustrated example, the impression logger 506 stores the impressionrecord 508 into the monitoring database 126. In some examples, theexample impression logger 506 credits the portion of the mediarepresented by the reference metadata 216. In some such examples, toassign credit to the portion of the media represented by the referencemetadata 216, the example impression logger 506 stores a value, sets aflag, and/or stores a tag in association with the impression recordindicative of the portion of the media being exposed to the householdrepresented by the meter ID 118.

While an example manner of implementing the example hash key identifier124 of FIG. 1 is illustrated in FIG. 5, one or more of the elements,processes and/or devices illustrated in FIG. 5 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example hybrid hash key analyzer 502, the example errorhandler 504, the example impression logger 506, and/or, more generally,the example hash key identifier 124 of FIG. 1 may be implemented byhardware, software, firmware and/or any combination of hardware,software and/or firmware. Thus, for example, any of the example hybridhash key analyzer 502, the example error handler 504, the exampleimpression logger 506, and/or, more generally, the example hash keyidentifier 124 could be implemented by one or more analog or digitalcircuit(s), logic circuits, programmable processor(s), applicationspecific integrated circuit(s) (ASIC(s)), programmable logic device(s)(PLD(s)) and/or field programmable logic device(s) (FPLD(s)). Whenreading any of the apparatus or system claims of this patent to cover apurely software and/or firmware implementation, at least one of theexample hybrid hash key analyzer 502, the example error handler 504,and/or the example impression logger 506 is/are hereby expressly definedto include a tangible computer readable storage device or storage disksuch as a memory, a digital versatile disk (DVD), a compact disk (CD), aBlu-ray disk, etc. storing the software and/or firmware. Further still,the example hash key identifier 124 of FIG. 1 may include one or moreelements, processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 5, and/or may include more than one of any or all ofthe illustrated elements, processes and devices.

Flowcharts representative of example machine readable instructions forimplementing the hash key identifier 124 of FIGS. 1 and 5 are shown inFIGS. 6 and 7. A flowchart representative of example machine readableinstructions for implementing the reference hash key generator 130 ofFIGS. 1 and 2 is shown in FIG. 8. In this example, the machine readableinstructions comprise programs for execution by a processor such as theprocessor 912 shown in the example processor platform 900 discussedbelow in connection with FIG. 9. The program may be embodied in softwarestored on a tangible computer readable storage medium such as a CD-ROM,a floppy disk, a hard drive, a digital versatile disk (DVD), a Blu-raydisk, or a memory associated with the processor 912, but the entireprogram and/or parts thereof could alternatively be executed by a deviceother than the processor 912 and/or embodied in firmware or dedicatedhardware. Further, although the example programs are described withreference to the flowcharts illustrated in FIGS. 6, 7, and/or 8, manyother methods of implementing the example hash key identifier 124 and/orthe example reference hash key generator 130 may alternatively be used.For example, the order of execution of the blocks may be changed, and/orsome of the blocks described may be changed, eliminated, or combined.

As mentioned above, the example processes of FIGS. 6, 7, and/or 8 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a tangible computer readable storagemedium such as a hard disk drive, a flash memory, a read-only memory(ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals and to exclude transmission media. Asused herein, “tangible computer readable storage medium” and “tangiblemachine readable storage medium” are used interchangeably. Additionallyor alternatively, the example processes of FIGS. 6, 7, and/or 8 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a non-transitory computer and/ormachine readable medium such as a hard disk drive, a flash memory, aread-only memory, a compact disk, a digital versatile disk, a cache, arandom-access memory and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media. As usedherein, when the phrase “at least” is used as the transition term in apreamble of a claim, it is open-ended in the same manner as the term“comprising” is open ended.

FIG. 6 is a flow diagram of example machine readable instructions thatmay be executed to implement the hash key identifier 124 of FIGS. 1and/or 5 to compare the exposure records 108 (FIGS. 1 and 5) to thereference records 202 (FIGS. 2, 3A, 3B, and 4). In the example processof FIG. 6, the metered hash keys 114 (FIGS. 1 and 5) and the referencehash keys 210 (FIGS. 2 and 3A) are not blurred. Initially, at block 602,the hybrid hash key analyzer 502 (FIG. 5) retrieves the next meteredexposure record 108 from the metering database 122 (FIGS. 1 and 5). Atblock 604, the hybrid hash key analyzer 502 determines whether themetered hash key 114 of the metered exposure record 108 retrieved atblock 602 corresponds to one of the reference records 202 in thereference database 128. For example, the example hybrid hash keyanalyzer 502 may query the reference database 128 using the metered hashkey 114. In such examples, if the reference database 128 returns areference record 202, the hybrid hash key analyzer 502 determines thatthe metered hash key 114 does substantially match or correspond to areference record 202 in the reference database 128. If the metered hashkey 114 corresponds to one of the reference records 202, program controladvances to block 605. Otherwise, if the metered hash key 114 does notcorrespond to one of the reference records 202, program control advancesto block 610. At block 605, the hybrid hash key analyzer 502 accessesthe reference record 202 from the reference database 128 correspondingto the metered hash key 114.

At block 606, the example error handler 504 (FIG. 5) determines whetherthe metered confirmation data 116 (FIG. 1) of the metered exposurerecord 108 retrieved at block 602 matches the reference confirmationdata 212 (FIGS. 2, 3A, 3B, and 4) of the reference record 202 accessedat block 605. In some examples, the error handler 504 performs a bitwisecomparison of the metered confirmation data 116 and the referenceconfirmation data 212 to generate an error level (e). In some suchexamples, the error handler 504 determines that the metered confirmationdata 116 matches the reference confirmation data 212 if the error level(e) satisfies (e.g., is less) than an error threshold. If the meteredconfirmation data 116 matches the reference confirmation data 212,program control advances to block 608. Otherwise, if the meteredconfirmation data 116 does not match the reference confirmation data212, program control advances to block 610.

At block 608, the example impression logger 506 (FIG. 5) generates animpression record based on the metered exposure record 108. For example,the impression logger 506 associates the meter ID 118 (FIG. 1)corresponding to the metered exposure record 108 with the referencemetadata 216 of the reference record 202. At block 610, the exampleimpression logger 1306 indicates that the metered exposure record 108 iserroneous. In some examples, the example impression logger 506 marks(e.g., sets a flag, etc.) the metered exposure record 108 as erroneousso that the metered exposure record 108 is not used to generate animpression record (e.g., the impression record 508 of FIG. 5).Alternatively, in some examples, the impression logger 506 discards themetered exposure record 108. At block 612, the hybrid hash key analyzer502 determines whether there is another exposure record 108 to analyze.If there is another metered exposure record 108 to analyze, programcontrol returns to block 602 to retrieve the next exposure record 108.Otherwise, if there is not another metered exposure record 108 toanalyze, the example program of FIG. 6 ends.

FIG. 7 is a flow diagram of example machine readable instructions thatmay be executed to implement the hash key identifier 124 of FIGS. 1and/or 5 to compare metered hash keys 114 (FIG. 1) corresponding to themetered exposure records 108 (FIGS. 1 and 5) to blurred reference hashkeys 214 (FIGS. 2, 3B, and 4) in the reference database 128 (FIG. 1).Initially, at block 702, the hybrid hash key analyzer 502 (FIG. 5)retrieves the next metered exposure record 108 from the meteringdatabase 122 (FIG. 1). At block 704, the hybrid hash key analyzer 502determines whether the metered hash key 114 of the metered exposurerecord 108 retrieved at block 702 corresponds to one of the referencerecords 202 in the reference database 128. For example, the examplehybrid hash key analyzer 502 may query the reference database 128 usingthe metered hash key 114. In such examples, if the reference database128 returns a reference record 202, the hybrid hash key analyzer 502determines that the metered hash key 114 does substantially match orcorrespond to a reference record 202 of the reference database 128. Ifthe metered hash key 114 corresponds to one of the reference records202, program control advances to block 705. Otherwise, if the meteredhash key 114 does not correspond to one of the reference records 202,program control advances to block 714. At block 705, the hybrid hash keyanalyzer 502 accesses the reference record 202 from the referencedatabase 128 corresponding to the metered hash key 114.

Because the blurred reference hash key 214 accessed at block 705 may beassociated with more than one portion of the media 104 and/or portion(s)of different media, the reference record 202 accessed at block 705 maybe associated with multiple candidate reference confirmationdata-reference metadata pairs ((e.g., the metadata 216 and the referenceconfirmation data 212 of FIG. 4). At block 706, the example errorhandler 504 retrieves the next candidate reference confirmationdata-reference metadata pair.

At block 708, the example error handler 504 determines whether themetered confirmation data 116 corresponding to the metered exposurerecord 108 retrieved at block 702 matches the candidate referenceconfirmation data 212 retrieved at block 706. For example, the errorhandler 504 may perform a bitwise comparison between the meteredconfirmation data 116 of the metered exposure record 108 selected atblock 702 and the candidate reference confirmation data 212 selected atblock 706 to generate an error level (e). In such examples, the errorhandler 504 determines that the metered confirmation data 116 matchesthe candidate reference confirmation data 212 if the error levelsatisfies (e.g., is less than) an error threshold (e). If the meteredconfirmation data 116 matches the candidate reference confirmation data212, program control advances to block 710. Otherwise, if the meteredconfirmation data 116 does not match the candidate referenceconfirmation data 212, program control advances to block 712. At block710, the example impression logger 506 (FIG. 5) generates an impressionrecord based on the metered exposure record 108. For example, theimpression logger 506 associates the meter ID 118 (FIG. 1) of themetered exposure record 108 with the reference metadata 216 associatedwith the candidate reference confirmation data 212 determined to bematching at block 708. Program control then advances to block 716.

At block 712, the example error handler 504 determines whether thereference record 202 retrieved at block 714 is associated with morecandidate reference confirmation data 212. If the reference record 202is associated with more candidate reference confirmation data 212,program control returns to block 706. Otherwise, if the reference record2002 is not associated with more candidate reference confirmation data212, program control advances to block 714.

At block 714, the example impression logger 506 indicates that themetered exposure record 108 is erroneous. In some examples, the exampleimpression logger 506 marks (e.g., sets a flag, etc.) the meteredexposure record 108 as erroneous so that the metered exposure record 108is not used to generate an impression record (e.g., the impressionrecord 508 of FIG. 5). Alternatively, in some examples, the impressionlogger 506 discards the metered exposure record 108. At block 716, thehybrid hash key analyzer 502 determines whether there is another meteredexposure record 108 to analyze. If there is another metered exposurerecord 108 to analyze, program control returns to block 702 to retrievethe next exposure record 108. Otherwise, if there is not another meteredexposure record 108 to analyze, the example program of FIG. 7 ends.

FIG. 8 is a flow diagram of example machine readable instructions thatmay be executed to implement the reference hash key generator 130 ofFIGS. 1 and/or 2 to generate reference records 202 (FIGS. 2, 3A, 3B, and4). Initially, at block 802, the hybrid hash key generator 204 (FIG. 2)generates samples of the reference media 132 (FIGS. 1, 2, and 4). Insome examples, the hybrid hash key generator 1004 continuously applies ahash function to the samples of the reference media 132 and places thehashed samples of the reference media 132 into, for example, a circularbuffer.

At block 804, the example hybrid hash key generator 204 selects a firstportion (e.g., the first portion 410 of FIG. 4) of the samples of thereference media 132. At block 805, the example hybrid hash key generator204 generates a reference hash key 210 based on the first portion 410 ofthe samples of the reference media 132 selected at block 804. Forexample, if the samples of the reference media 132 have a length of8-bits and the reference hash key is to have a length of 40-bits, thehybrid hash key generator 204 selects the next five samples (e.g.,sample N₀ through N₄) of the reference media 132 as the reference hashkey 1010. When the next reference hash key 210 is generated, the examplehybrid hash key generator 204 selects five additional samples of thereference media 132, some of which may overlap with the previouslygenerated reference hash key 210. For example, a first reference hashkey (k) 210 may include samples N₁₀ through N₁₄, and a second referencehash key (k+1) 210 may include samples N₁₁ through N₁₅.

At block 806, the example hybrid hash key generator 204 selects a secondportion (e.g., the second portion 416 of FIG. 4) of the samples of thereference media 132 to generate reference confirmation data 212 (FIGS.2, 3A, 3B and 4). The example hybrid hash key generator 204 selects thesecond portion 416 based on an offset (e.g., the offset 418 of FIG. 4)and a size (e.g., the size 420 of FIG. 4) set by the AME 102 (FIG. 1).For example if the offset 416 is −16 bits (−2 bytes), the size 420 isfive bytes, and the reference hash key 210 was generated from samplesN₁₂ through N₁₆, the confirmation data 212 is generated using samples N₈through N₁₃.

At block 808, the example hash key modifier 204 (FIG. 2) determineswhether to apply the blurring function to the reference hash key 210generated at block 805. If the example hash key modifier 204 is to applythe blurring function to the reference hash key 210, program controladvances to block 812. Otherwise, if the example hash key modifier 204is not to apply the blurring function to the reference hash key 210,program control advances to block 810. At block 810, the examplereference generator 208 (FIG. 2) generates a reference record 202 byassociating the reference hash key 210 generated at block 805 with (i)reference metadata 216 corresponding to the first portion of thereference media 132 obtained at block 804 to generate the reference hashkey 210, and (ii) the reference confirmation data 212 selected at block806. For example, the reference hash key 210 may correspond to a stationwith the call sign WSNS, a date of Sep. 18, 2015, and a timestamp of14:06:52.0825.

At block 812, the example hash key modifier 204 applies the blurringfunction to the reference hash key 210 to generate a blurred referencehash key 214 (FIGS. 2, 3B and 4). To apply the blurring function in theillustrated example, the example hash key modifier 204 sets a number ofthe least significant bits of each byte of the reference hash key 210 tozero. For example, if the reference hash key 210 is 0xC3 41 D2 52(binary: 11000011 01000001 11010010 01010010) and the two leastsignificant bits of each byte are set to zero by the blurring function,the blurred reference hash key 214 is 0xC0 40 D0 50 (binary: 1100000001000000 11010000 01010000). Alternatively, if only the leastsignificant bit of each byte is set to zero by the blurring function,the blurred reference hash key 214 is 0xC2 40 D2 52 (binary: 1100001001000000 11010010 01010010). At block 814, the example referencegenerator 208 generates a reference record 202 by associating theblurred reference hash key 214 generated at block 812 with (i) referencemetadata 216 corresponding to the first portion of the reference media132 used to generate the reference hash key 210, and (ii) the referenceconfirmation data 212 selected at block 806.

At block 816, the example hybrid hash key generator 204 determineswhether another reference record 202 is to be generated. For example, ifall the reference hash keys 210 for the reference media 132 have beengenerated (e.g., the hybrid hash key generator 204 has reached the endof the reference media 132), the hybrid hash key generator 204determines that another record 202 is not to be generated. If anotherreference record 202 is to be generated, program control returns toblock 804. Otherwise, if another reference hash key 210 or blurredreference hash key 214 is not to be generated, the program ends.

FIG. 9 is a block diagram of an example processor platform 900 capableof executing the instructions of FIGS. 6, 7 and/or 8 to implement thehash key identifier 124 of FIGS. 1 and 5, and/or the reference hash keygenerator 130 of FIGS. 1 and 2. The processor platform 900 can be, forexample, a server, a personal computer, a workstation, or any other typeof computing device.

The processor platform 900 of the illustrated example includes aprocessor 912. The processor 912 of the illustrated example is hardware.For example, the processor 912 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors or controllers fromany desired family or manufacturer. In the illustrated example, theprocessor 912 is structured to include the example hybrid hash keyanalyzer 502, the example error handler 504, and the example 505.Additionally or alternatively, in some examples, the processor 912 isstructured to include the example hybrid hash key generator 204, theexample hash key modifier 206, and the example reference generator 208.

The processor 912 of the illustrated example includes a local memory 913(e.g., a cache). The processor 912 of the illustrated example is incommunication with a main memory including a volatile memory 914 and anon-volatile memory 916 via a bus 918. The volatile memory 914 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM)and/or any other type of random access memory device. The non-volatilememory 916 may be implemented by flash memory and/or any other desiredtype of memory device. Access to the main memory 914, 916 is controlledby a memory controller.

The processor platform 900 of the illustrated example also includes aninterface circuit 920. The interface circuit 920 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 922 are connectedto the interface circuit 920. The input device(s) 922 permit(s) a userto enter data and commands into the processor 912. The input device(s)can be implemented by, for example, an audio sensor, a microphone, acamera (still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, isopoint and/or a voice recognition system.

One or more output devices 924 are also connected to the interfacecircuit 920 of the illustrated example. The output devices 924 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a printer).The interface circuit 920 of the illustrated example, thus, typicallyincludes a graphics driver card, a graphics driver chip or a graphicsdriver processor.

The interface circuit 920 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network926 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 900 of the illustrated example also includes oneor more mass storage devices 928 for storing software and/or data.Examples of such mass storage devices 928 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAIDsystems, and digital versatile disk (DVD) drives.

Coded instructions 932 of FIGS. 6, 7 and/or 8 may be stored in the massstorage device 928, in the volatile memory 914, in the non-volatilememory 916, and/or on a removable tangible computer readable storagemedium such as a CD or DVD.

From the foregoing, it will appreciate that examples have been disclosedwhich allow error-tolerant identification of metered hash keys producedfrom media sources that introduce noise into the metered hash keys.Additionally, examples have been disclosed which generate referencerecords that include information pertaining to additionally portions ofa medium. Examples have been disclosed which increase the accuracy ofimpression data and reduce processing (e.g., reduce the burden on asemiconductor based processor) required to perform a match and/or toadjust for erroneous and/or missing impression data. Moreover, becauseerroneous hash keys can be identified efficiently, search time in adatabase to identify media is reduced. Reducing search time savesprocessing resources and reduces the energy consumption required toperform media monitoring.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

1. A method comprising: generating a hash key based on first samples ofmedia, the first samples corresponding to a portion of the media sampledin a buffer of a computing device; applying a blurring function to thehash key to generate a blurred hash key; generating first confirmationdata based on second samples of the media; storing the blurred hash keyin association with the first confirmation data and first reference datain a memory separate from the buffer of the sampled media, the firstreference data representative of the portion of the media; and creditingthe portion of the media with an exposure when a metered hash keymatches the blurred hash key and metered confirmation data associatedwith the metered hash key matches the first confirmation data.
 2. Amethod as defined in claim 1, wherein the second samples are offset by anumber of bits from an end of the portion of the media.
 3. A method asdefined in claim 1, wherein the portion of the media overlaps a secondportion of the media corresponding to the second samples.
 4. A method asdefined in claim 1, further including setting the least significant bitof bytes of the hash key to zero.
 5. A method as defined in claim 1,wherein the blurred hash key is stored in association with secondconfirmation data that is associated with second reference data.
 6. Anapparatus comprising: a hybrid hash key generator to: generate a hashkey based on first samples of media, the first samples corresponding toa portion of the media sampled in a buffer of a computing device; andgenerate first confirmation data based on second samples of the media; ahash key modifier to apply a blurring function to the hash key togenerate a blurred hash key; and a memory to store the blurred hash keyin association with the first confirmation data and first referencedata, the first reference data representative of the portion of themedia.
 7. An apparatus as defined in claim 6, further including a hashkey identifier to credit the portion of the media with an exposure whena metered hash key matches the blurred hash key and metered confirmationdata associated with the metered hash key matches the first confirmationdata.
 8. An apparatus as defined in claim 6, wherein the second samplesare offset by a number of bits from an end of the portion of the media.9. An apparatus as defined in claim 6, wherein the portion of the mediaoverlaps with a second portion corresponding to the second samples. 10.An apparatus as defined in claim 6, wherein the hash key modifier isfurther to set the least significant bit of bytes of the hash key tozero.
 11. An apparatus as defined in claim 6, wherein the blurred hashkey is stored in association with second confirmation data that isassociated with second reference data.
 12. A tangible computer readablestorage medium comprising machine readable instructions that, whenexecuted, cause a machine to at least: generate a hash key based onfirst samples of media, the first samples corresponding to a portion ofthe media sampled in a buffer of a computing device; apply a blurringfunction to the hash key to generate a blurred hash key; generate firstconfirmation data based on second samples of the media; store theblurred hash key in association with the first confirmation data andfirst reference data in a memory separate from the buffer of the sampledmedia, the first reference data identifying the portion of the media;and credit the portion of the media with an exposure when a metered hashkey matches the blurred hash key and metered confirmation dataassociated with the metered hash key matches the first confirmationdata.
 13. A tangible computer readable storage medium as defined inclaim 12, wherein the second samples are offset by a number of bits froman end of the portion of the media.
 14. A tangible computer readablestorage medium as defined in claim 12, wherein the portion of the mediaoverlaps with a second portion corresponding to the second samples. 15.A tangible computer readable storage medium as defined in claim 12,wherein the instructions further cause the machine to set the leastsignificant bit of bytes of the hash key to zero.
 16. A tangiblecomputer readable storage medium as defined in claim 12, wherein theblurred hash key is stored in association with second confirmation datathat is associated with second reference data. 17.-37. (canceled)